DocumentCode :
2957131
Title :
Analog integrated circuit parameter fault diagnosis using artificial neural network
Author :
Jingfan Zhang ; Junren Gan ; Linsheng Yao
Author_Institution :
Inst. of Metall., Acad. Sinica, Shanghai
fYear :
1996
fDate :
21-24 Oct 1996
Firstpage :
400
Lastpage :
403
Abstract :
An artificial neural network method used for analog IC parameter fault diagnosis is presented in this paper. It is fast and accurate. Therefore it has boundless prospects in the field of analog IC parameter fault diagnosis. With the rapid development in IC technology, the fault diagnosis problem of analog IC has become more acute. The traditional methods´ computation complexity and inaccuracy of results make most of them still unacceptable. We therefore research and develop an artificial neural network system to resolving the low velocity and low measurability problem of the traditional methods
Keywords :
analogue integrated circuits; fault diagnosis; integrated circuit testing; network parameters; neural nets; analog integrated circuit parameter fault diagnosis; artificial neural network; Analog integrated circuits; Artificial neural networks; Backpropagation algorithms; Circuit simulation; Circuit testing; Computer networks; Fault diagnosis; Linear circuits; Neural networks; Reflection;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
ASIC, 1996., 2nd International Conference on
Conference_Location :
Shanghai
Print_ISBN :
7-5439-0940-5
Type :
conf
DOI :
10.1109/ICASIC.1996.562837
Filename :
562837
Link To Document :
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